The increasing prevalence of laminated composite materials in aircraft construction has spawned a need for a method that can be implemented in real-time and is not prohibitively time consuming. Impacts to composite structures may cause subsurface damages, not visible to the naked eye, in the form of ply delamination, core crushing and matrix debonding. Current methods of inspection include labor intensive x-ray examinations and subjective coin tap tests, neither of which can be performed while in flight.
Identification methods have been proposed and demonstrated to detect impact magnitudes and locations. However, these methods are restrictive in that they use an accurate first principles-based model of the structure being monitored, large sensor arrays, carefully controlled boundary conditions or a combination of the above.
The heterogeneous nature of the helicopter introduces difficulties with applying the frequency domain location identification methods developed on relatively homogeneous composite specimens. The exterior of the helicopter used as a test specimen has surfaces including retrofitted carbon fiber-reinforced composite honeycomb panels, plastic windows, doors, aluminum skin with rib stiffening, and repaired sections. This wide range of outer panel stiffnesses means impacts' pulse widths, and therefore frequency bandwidths, may vary between impacts at different locations. The widely varying frequency excitation bandwidth of impacts to this heterogeneous structure makes defining a small frequency range of interest to use for comparison difficult.
Various embodiments of the present invention provide novel and nonobvious ways of detecting impact magnitudes and locations.
A critical challenge in fielding composite aerospace structures is the need to locate impact damage that often offers little to no visual indication. The inspection of large composite aircraft using existing methodologies is labor-intensive and costly, but by identifying the severity of impacts through position and force identification of these impacts, inspections could be more focused and potentially more frequent, allowing for a reduction of inspection cost and an increase in safety. To this end, impact identification methods attempt to determine impact force locations and magnitudes. Strategies for using a sparse sensor array allows such a system to be implemented with little hardware, in order to minimize the cost and space requirements of such a system. New entropy-based and randomness-based methods of impact identification are presented, and the effects of several sources of error are addressed. By simulating some of the limitations and challenges of the field environment, the relevant sources of error can be identified and compensated for. Strategies for addressing these issues are presented with two case studies: a composite filament-wound rocket motor casing and a heavy lift helicopter. The randomness-based impact identification method was shown to locate more than 96% of impacts to a helicopter fuselage to either the correct impact point or an adjacent point. Methods for identifying multiple impacts were developed, and impacts acting in rapid succession were located within two grid points of the actual location in 87.6% of cases, with similar average force estimation error to when only one impact acts.